High impedance fault detection method based on Data divergence in the distribution network

The fault current caused by a high impedance fault is not sufficient to trigger overcurrent protection relays, which may lead to serious power accidents, fires, or even explosions in the distribution network, resulting in casualties as well as significant economic losses.This paper proposes a high impedance fault detection method using Wasserstein distance metric. Firstly, we obtain the corresponding principal components from the measurement data matrix by principal component analysis. Secondly, we segment the resulting first principal component through the data window and calculate the Wasserstein distance between the data distribution of the first principal component and the normal reference principal component. Finally, the distance measurement results are judged by the threshold line and the judgment time to detect the HIF in the system. Simulation results and field measurement results verified the performance of the proposed method.